Top Hybrid Machine Learning Engineer Jobs

The Staff Applied AI/ML Engineer will develop, test, and deploy AI/ML models, transition models to production, and collaborate with teams to align solutions with business needs.

Lead Machine Learning Engineer responsible for designing and maintaining AI platforms, collaborating with teams, and ensuring best practices in AI/ML technologies and cloud infrastructure.

As a Machine Learning Subject Matter Expert, analyze ML systems, validate claims, evaluate model performance, and collaborate with teams to report findings.

The Machine Learning Engineer will develop and optimize large-scale ML models, build low-latency inference pipelines, and collaborate with teams to enhance performance and automate ML processes.

The Machine Learning Engineer will lead the development of a semantic intelligence platform, building knowledge graphs and AI software to enhance data accessibility and business insights.

Lead the Applied Machine Learning team to develop AI solutions for customer service, focusing on voice-specific ML models and infrastructure management.

The Senior Machine Learning Engineer will develop foundational models for recommendations, mentor engineers, and collaborate on improving user experiences with machine learning.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

As a Senior Machine Learning Engineer in the Health team, you'll design and productionize ML systems for personalized health metrics, collaborating with data scientists and engineers to optimize performance and ensure service reliability.

As a Senior Machine Learning Engineer, you will develop machine learning models, manage their lifecycle, build infrastructure, and collaborate with teams to enhance our capabilities in various ML areas.